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Broad learning through fusions = an ...
~
Zhang, Jiawei.
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博客來
Broad learning through fusions = an application on social networks /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Broad learning through fusions/ by Jiawei Zhang, Philip S. Yu.
Reminder of title:
an application on social networks /
Author:
Zhang, Jiawei.
other author:
Yu, Philip S.
Published:
Cham :Springer International Publishing : : 2019.,
Description:
xv, 419 p. :ill., digital ;24 cm.
[NT 15003449]:
1 Broad Learning Introduction -- 2 Machine Learning Overview -- 3 Social Network Overview -- 4 Supervised Network Alignment -- 5 Unsupervised Network Alignment -- 6 Semi-supervised Network Alignment -- 7 Link Prediction -- 8 Community Detection -- 9 Information Diffusion -- 10 Viral Marketing -- 11 Network Embedding -- 12 Frontier and Future Directions -- References.
Contained By:
Springer eBooks
Subject:
Data mining. -
Online resource:
https://doi.org/10.1007/978-3-030-12528-8
ISBN:
9783030125288
Broad learning through fusions = an application on social networks /
Zhang, Jiawei.
Broad learning through fusions
an application on social networks /[electronic resource] :by Jiawei Zhang, Philip S. Yu. - Cham :Springer International Publishing :2019. - xv, 419 p. :ill., digital ;24 cm.
1 Broad Learning Introduction -- 2 Machine Learning Overview -- 3 Social Network Overview -- 4 Supervised Network Alignment -- 5 Unsupervised Network Alignment -- 6 Semi-supervised Network Alignment -- 7 Link Prediction -- 8 Community Detection -- 9 Information Diffusion -- 10 Viral Marketing -- 11 Network Embedding -- 12 Frontier and Future Directions -- References.
This book offers a clear and comprehensive introduction to broad learning, one of the novel learning problems studied in data mining and machine learning. Broad learning aims at fusing multiple large-scale information sources of diverse varieties together, and carrying out synergistic data mining tasks across these fused sources in one unified analytic. This book takes online social networks as an application example to introduce the latest alignment and knowledge discovery algorithms. Besides the overview of broad learning, machine learning and social network basics, specific topics covered in this book include network alignment, link prediction, community detection, information diffusion, viral marketing, and network embedding.
ISBN: 9783030125288
Standard No.: 10.1007/978-3-030-12528-8doiSubjects--Topical Terms:
562972
Data mining.
LC Class. No.: QA76.9.D343 / Z43 2019
Dewey Class. No.: 006.312
Broad learning through fusions = an application on social networks /
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1 Broad Learning Introduction -- 2 Machine Learning Overview -- 3 Social Network Overview -- 4 Supervised Network Alignment -- 5 Unsupervised Network Alignment -- 6 Semi-supervised Network Alignment -- 7 Link Prediction -- 8 Community Detection -- 9 Information Diffusion -- 10 Viral Marketing -- 11 Network Embedding -- 12 Frontier and Future Directions -- References.
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This book offers a clear and comprehensive introduction to broad learning, one of the novel learning problems studied in data mining and machine learning. Broad learning aims at fusing multiple large-scale information sources of diverse varieties together, and carrying out synergistic data mining tasks across these fused sources in one unified analytic. This book takes online social networks as an application example to introduce the latest alignment and knowledge discovery algorithms. Besides the overview of broad learning, machine learning and social network basics, specific topics covered in this book include network alignment, link prediction, community detection, information diffusion, viral marketing, and network embedding.
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Computer Science (Springer-11645)
based on 0 review(s)
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W9374574
電子資源
11.線上閱覽_V
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EB QA76.9.D343 Z43 2019
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